Future Internet2016, 8(2), 23; doi:10.3390/fi8020023 - published 20 May 2016 Show/Hide Abstract
Abstract: A smart city is an environment where a pervasive, multi-service network is employed to provide citizens improved living conditions as well as better public safety and security. Advanced communication technologies are essential to achieve this goal. In particular, an efficient and reliable communication network plays a crucial role in providing continue, ubiquitous, and reliable interconnections among users, smart devices, and applications. As a consequence, wireless networking appears as the principal enabling communication technology despite the necessity to face severe challenges to satisfy the needs arising from a smart environment, such as explosive data volume, heterogeneous data traffic, and support of quality of service constraints. An interesting approach for meeting the growing data demand due to smart city applications is to adopt suitable methodologies to improve the usage of all potential spectrum resources. Towards this goal, a very promising solution is represented by the Cognitive Radio technology that enables context-aware capability in order to pursue an efficient use of the available communication resources according to the surrounding environment conditions. In this paper we provide a review of the characteristics, challenges, and solutions of a smart city communication architecture, based on the Cognitive Radio technology, by focusing on two new network paradigms—namely, Heterogeneous Network and Machines-to-Machines communications—that are of special interest to efficiently support smart city applications and services.
Future Internet2016, 8(2), 22; doi:10.3390/fi8020022 - published 18 May 2016 Show/Hide Abstract
Abstract: The concept of competence, which emerged during the reform of computer engineering degrees, has not brought benefits to companies when attempting to select the most suitable candidates for their jobs. This article aims to show some of the research that has been conducted to determine why companies have not found these skills useful and how both can be aligned. Finally, we show the development of an Expert System that will enable companies to select the most suitable candidates for their jobs, considering personal and social skills, along with technical knowledge. This prototype will serve as a basis to align the competencies defined in the curricula with professional requirements, thus allowing a true alignment between degree courses and the needs of professional companies.
Future Internet2016, 8(2), 20; doi:10.3390/fi8020020 - published 17 May 2016 Show/Hide Abstract
Abstract: For many individuals and organizations, cyber-insurance is the most practical and only way of handling a major financial impact of an information security event. However, the cyber-insurance market suffers from the problem of information asymmetry, lack of product diversity, illiquidity, high transaction cost, and so on. On the other hand, in theory, capital market-based financial instruments can provide a risk transfer mechanism with the ability to absorb the adverse impact of an information security event. Thus, this article addresses the limitations in the cyber-(re)insurance markets with a set of capital market-based financial instruments. This article presents a set of information security derivatives, namely options, vanilla options, swap, and futures that can be traded at an information security prediction market. Furthermore, this article demonstrates the usefulness of information security derivatives in a given scenario and presents an evaluation of the same in comparison with cyber-insurance. In our analysis, we found that the information security derivatives can at least be a partial solution to the problems in the cyber-insurance markets. The information security derivatives can be used as an effective tool for information elicitation and aggregation, cyber risk pricing, risk hedging, and strategic decision making for information security risk management.
Future Internet2016, 8(2), 21; doi:10.3390/fi8020021 - published 13 May 2016 Show/Hide Abstract
Abstract: The many decisions that people make about what to pay attention to online shape the spread of information in online social networks. Due to the constraints of available time and cognitive resources, the ease of discovery strongly impacts how people allocate their attention to social media content. As a consequence, the position of information in an individual’s social feed, as well as explicit social signals about its popularity, determine whether it will be seen, and the likelihood that it will be shared with followers. Accounting for these cognitive limits simplifies mechanics of information diffusion in online social networks and explains puzzling empirical observations: (i) information generally fails to spread in social media and (ii) highly connected people are less likely to re-share information. Studies of information diffusion on different social media platforms reviewed here suggest that the interplay between human cognitive limits and network structure differentiates the spread of information from other social contagions, such as the spread of a virus through a population.
Future Internet2016, 8(2), 19; doi:10.3390/fi8020019 - published 12 May 2016 Show/Hide Abstract
Abstract: In the last 20 years, the convergence of different factors—the rise of the complexity of science, the “data deluge” and the advances in information technologies—triggered a paradigm shift in the way we understand complex social systems and their evolution. Beyond shedding new light onto social dynamics, the emerging research area of Computational Social Science (CSS) is providing a new rationale for a more scientifically-grounded and effective policy design. The paper discusses the opportunities potentially deriving from the intersection between policy design issues and CSS methods. After a general introduction to the limits of traditional policy-making and a brief review of the most promising CSS methodologies, the work deals with way in which the insights potentially offered by CSS can concretely flow in policy choices. The attention is focused, to this end, on the legal mechanisms regulating the formulation and the evaluation of public policies. Our goal is two-fold: sketch how the project of a “smart society” is connected to the evolution of social sciences and emphasize the need for change in the way in which public policies are conceived of, designed and implemented.
Future Internet2016, 8(2), 18; doi:10.3390/fi8020018 - published 11 May 2016 Show/Hide Abstract
Abstract: Internet of Things (IoT) seems a viable way to enable the Smart Cities of the future. iNUIT (Internet of Things for Urban Innovation) is a multi-year research program that aims to create an ecosystem that exploits the variety of data coming from multiple sensors and connected objects installed on the scale of a city, in order to meet specific needs in terms of development of new services (physical security, resource management, etc.). Among the multiple research activities within iNUIT, we present two projects: SmartCrowd and OpEc. SmartCrowd aims at monitoring the crowd’s movement during large events. It focuses on real-time tracking using sensors available in smartphones and on the use of a crowd simulator to detect possible dangerous scenarios. A proof-of-concept of the application has been tested at the Paléo Festival (Switzerland) showing the feasibility of the approach. OpEc (Optimisation de l’Eclairage public) aims at using IoT to implement dynamic street light management and control with the goal of reducing street light energy consumption while guaranteeing the same level of security of traditional illumination. The system has been tested during two months in a street in St-Imier (Switzerland) without interruption, validating its stability and resulting in an overall energy saving of about 56%.